{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Table of Contents](./table_of_contents.ipynb)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# The Extended Kalman Filter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from __future__ import division, print_function\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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     "execution_count": 2,
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   ],
   "source": [
    "#format the book\n",
    "import book_format\n",
    "book_format.set_style()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have developed the theory for the linear Kalman filter. Then, in the last two chapters we broached the topic of using Kalman filters for nonlinear problems. In this chapter we will learn the Extended Kalman filter (EKF). The EKF handles nonlinearity by linearizing the system at the point of the current estimate, and then the linear Kalman filter is used to filter this linearized system. It was one of the very first techniques used for nonlinear problems, and it remains the most common technique. \n",
    "\n",
    "The EKF provides significant mathematical challenges to the designer of the filter; this is the most challenging chapter of the book. I do everything I can to avoid the EKF in favor of other techniques that have been developed to filter nonlinear problems. However, the topic is unavoidable; all classic papers and a majority of current papers in the field use the EKF. Even if you do not use the EKF in your own work you will need to be familiar with the topic to be able to read the literature. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Linearizing the Kalman Filter\n",
    "\n",
    "The Kalman filter uses linear equations, so it does not work with nonlinear problems. Problems can be nonlinear in two ways. First, the process model might be nonlinear. An object falling through the atmosphere encounters drag which reduces its acceleration. The drag coefficient varies based on the velocity the object. The resulting behavior is nonlinear - it cannot be modeled with linear equations. Second, the measurements could be nonlinear. For example, a radar gives a range and bearing to a target. We use trigonometry, which is nonlinear, to compute the position of the target.\n",
    "\n",
    "For the linear filter we have these equations for the process and measurement models:\n",
    "\n",
    "$$\\begin{aligned}\\dot{\\mathbf x} &= \\mathbf{Ax} + w_x\\\\\n",
    "\\mathbf z &= \\mathbf{Hx} + w_z\n",
    "\\end{aligned}$$\n",
    "\n",
    "Where $\\mathbf A$ is the systems dynamic matrix. Using the state space methods covered in the **Kalman Filter Math** chapter these equations can be tranformed into \n",
    "$$\\begin{aligned}\\bar{\\mathbf x} &= \\mathbf{Fx} \\\\\n",
    "\\mathbf z &= \\mathbf{Hx}\n",
    "\\end{aligned}$$\n",
    "\n",
    "where $\\mathbf F$ is the *fundamental matrix*. The noise $w_x$ and $w_z$ terms are incorporated into the matrices $\\mathbf R$ and $\\mathbf Q$. This form of the equations allow us to compute the state at step $k$ given a measurement at step $k$ and the state estimate at step $k-1$. In earlier chapters I built your intuition and minimized the math by using problems describable with Newton's equations. We know how to design $\\mathbf F$ based on high school physics.\n",
    "\n",
    "\n",
    "For the nonlinear model the linear expression $\\mathbf{Fx} + \\mathbf{Bu}$ is replaced by a nonlinear function $f(\\mathbf x, \\mathbf u)$, and the linear expression $\\mathbf{Hx}$ is replaced by a nonlinear function $h(\\mathbf x)$:\n",
    "\n",
    "$$\\begin{aligned}\\dot{\\mathbf x} &= f(\\mathbf x, \\mathbf u) + w_x\\\\\n",
    "\\mathbf z &= h(\\mathbf x) + w_z\n",
    "\\end{aligned}$$\n",
    "\n",
    "You might imagine that we could proceed by finding a new set of Kalman filter equations that optimally solve these equations. But if you remember the charts in the **Nonlinear Filtering** chapter you'll recall that passing a Gaussian through a nonlinear function results in a probability distribution that is no longer Gaussian. So this will not work.\n",
    "\n",
    "The EKF does not alter the Kalman filter's linear equations. Instead, it *linearizes* the nonlinear equations at the point of the current estimate, and uses this linearization in the linear Kalman filter. \n",
    "\n",
    "*Linearize* means what it sounds like. We find a line that most closely matches the curve at a defined point. The graph below linearizes the parabola $f(x)=x^2-2x$ at $x=1.5$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import kf_book.ekf_internal as ekf_internal\n",
    "ekf_internal.show_linearization()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If the curve above is the process model, then the dotted lines shows the linearization of that curve for the estimate $x=1.5$.\n",
    "\n",
    "We linearize systems by taking the derivative, which finds the slope of a curve:\n",
    "\n",
    "$$\\begin{aligned}\n",
    "f(x) &= x^2 -2x \\\\\n",
    "\\frac{df}{dx} &= 2x - 2\n",
    "\\end{aligned}$$\n",
    "\n",
    "and then evaluating it at $x$:\n",
    "\n",
    "$$\\begin{aligned}m &= f'(x=1.5) \\\\&= 2(1.5) - 2 \\\\&= 1\\end{aligned}$$ \n",
    "\n",
    "Linearizing systems of differential equations is similar. We linearize $f(\\mathbf x, \\mathbf u)$, and $h(\\mathbf x)$ by taking the partial derivatives of each to evaluate $\\mathbf F$ and $\\mathbf H$ at the point $\\mathbf x_t$ and $\\mathbf u_t$. We call the partial derivative of a matrix the [*Jacobian*](https://en.wikipedia.org/wiki/Jacobian_matrix_and_determinant). This gives us the the discrete state transition matrix and measurement model matrix:\n",
    "\n",
    "$$\n",
    "\\begin{aligned}\n",
    "\\mathbf F \n",
    "&= {\\frac{\\partial{f(\\mathbf x_t, \\mathbf u_t)}}{\\partial{\\mathbf x}}}\\biggr|_{{\\mathbf x_t},{\\mathbf u_t}} \\\\\n",
    "\\mathbf H &= \\frac{\\partial{h(\\bar{\\mathbf x}_t)}}{\\partial{\\bar{\\mathbf x}}}\\biggr|_{\\bar{\\mathbf x}_t} \n",
    "\\end{aligned}\n",
    "$$\n",
    "\n",
    "This leads to the following equations for the EKF. I put boxes around the differences from the linear filter:\n",
    "\n",
    "$$\\begin{array}{l|l}\n",
    "\\text{linear Kalman filter} & \\text{EKF} \\\\\n",
    "\\hline \n",
    "& \\boxed{\\mathbf F = {\\frac{\\partial{f(\\mathbf x_t, \\mathbf u_t)}}{\\partial{\\mathbf x}}}\\biggr|_{{\\mathbf x_t},{\\mathbf u_t}}} \\\\\n",
    "\\mathbf{\\bar x} = \\mathbf{Fx} + \\mathbf{Bu} & \\boxed{\\mathbf{\\bar x} = f(\\mathbf x, \\mathbf u)}  \\\\\n",
    "\\mathbf{\\bar P} = \\mathbf{FPF}^\\mathsf{T}+\\mathbf Q  & \\mathbf{\\bar P} = \\mathbf{FPF}^\\mathsf{T}+\\mathbf Q \\\\\n",
    "\\hline\n",
    "& \\boxed{\\mathbf H = \\frac{\\partial{h(\\bar{\\mathbf x}_t)}}{\\partial{\\bar{\\mathbf x}}}\\biggr|_{\\bar{\\mathbf x}_t}} \\\\\n",
    "\\textbf{y} = \\mathbf z - \\mathbf{H \\bar{x}} & \\textbf{y} = \\mathbf z - \\boxed{h(\\bar{x})}\\\\\n",
    "\\mathbf{K} = \\mathbf{\\bar{P}H}^\\mathsf{T} (\\mathbf{H\\bar{P}H}^\\mathsf{T} + \\mathbf R)^{-1} & \\mathbf{K} = \\mathbf{\\bar{P}H}^\\mathsf{T} (\\mathbf{H\\bar{P}H}^\\mathsf{T} + \\mathbf R)^{-1} \\\\\n",
    "\\mathbf x=\\mathbf{\\bar{x}} +\\mathbf{K\\textbf{y}} & \\mathbf x=\\mathbf{\\bar{x}} +\\mathbf{K\\textbf{y}} \\\\\n",
    "\\mathbf P= (\\mathbf{I}-\\mathbf{KH})\\mathbf{\\bar{P}} & \\mathbf P= (\\mathbf{I}-\\mathbf{KH})\\mathbf{\\bar{P}}\n",
    "\\end{array}$$\n",
    "\n",
    "We don't normally use $\\mathbf{Fx}$ to propagate the state for the EKF as the linearization causes inaccuracies. It is typical to compute $\\bar{\\mathbf x}$ using a suitable numerical integration technique such as Euler or Runge Kutta. Thus I wrote $\\mathbf{\\bar x} = f(\\mathbf x, \\mathbf u)$. For the same reasons we don't use $\\mathbf{H\\bar{x}}$ in the computation for the residual, opting for the more accurate $h(\\bar{\\mathbf x})$.\n",
    "\n",
    "I think the easiest way to understand the EKF is to start off with an example. Later you may want to come back and reread this section."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example: Tracking a Airplane\n",
    "\n",
    "This example tracks an airplane using ground based radar. We implemented a UKF for this problem in the last chapter. Now we will implement an EKF for the same problem so we can compare both the filter performance and the level of effort required to implement the filter.\n",
    "\n",
    "Radars work by emitting a beam of radio waves and scanning for a return bounce. Anything in the beam's path will reflects some of the signal back to the radar. By timing how long it takes for the reflected signal to get back to the radar the system can compute the *slant distance* - the straight line distance from the radar installation to the object.\n",
    "\n",
    "The relationship between the radar's slant range distance $r$ and elevation angle $\\epsilon$ with the horizontal position $x$ and altitude $y$ of the aircraft is illustrated in the figure below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ekf_internal.show_radar_chart()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This gives us the equalities:\n",
    "\n",
    "$$\\begin{aligned}\n",
    "\\epsilon &= \\tan^{-1} \\frac y x\\\\\n",
    "r^2 &= x^2 + y^2\n",
    "\\end{aligned}$$ "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Design the State Variables\n",
    "\n",
    "We want to track the position of an aircraft assuming a constant velocity and altitude, and measurements of the slant distance to the aircraft. That means we need 3 state variables - horizontal distance, horizonal velocity, and altitude:\n",
    "\n",
    "$$\\mathbf x = \\begin{bmatrix}\\mathtt{distance} \\\\\\mathtt{velocity}\\\\ \\mathtt{altitude}\\end{bmatrix}=    \\begin{bmatrix}x \\\\ \\dot x\\\\ y\\end{bmatrix}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Design the Process Model\n",
    "\n",
    "We assume a Newtonian, kinematic system for the aircraft. We've used this model in previous chapters, so by inspection you may recognize that we want\n",
    "\n",
    "$$\\mathbf F = \\left[\\begin{array}{cc|c} 1 & \\Delta t & 0\\\\\n",
    "0 & 1 & 0 \\\\ \\hline\n",
    "0 & 0 & 1\\end{array}\\right]$$\n",
    "\n",
    "I've partioned the matrix into blocks to show the upper left block is a constant velocity model for $x$, and the lower right block is a constant position model for $y$.\n",
    "\n",
    "However, let's practice finding these matrices. We model systems with a set of differential equations. We need an equation in the form \n",
    "\n",
    "$$\\dot{\\mathbf x} = \\mathbf{Ax} + \\mathbf{w}$$\n",
    "where $\\mathbf{w}$ is the system noise. \n",
    "\n",
    "The variables $x$ and $y$ are independent so we can compute them separately. The differential equations for motion in one dimension are:\n",
    "\n",
    "$$\\begin{aligned}v &= \\dot x \\\\\n",
    "a &= \\ddot{x} = 0\\end{aligned}$$\n",
    "\n",
    "Now we put the differential equations into state-space form. If this was a second or greater order differential system we would have to first reduce them to an equivalent set of first degree equations. The equations are first order, so we put them in state space matrix form as\n",
    "\n",
    "$$\\begin{aligned}\\begin{bmatrix}\\dot x \\\\ \\ddot{x}\\end{bmatrix} &= \\begin{bmatrix}0&1\\\\0&0\\end{bmatrix} \\begin{bmatrix}x \\\\ \n",
    "\\dot x\\end{bmatrix} \\\\ \\dot{\\mathbf x} &= \\mathbf{Ax}\\end{aligned}$$\n",
    "where $\\mathbf A=\\begin{bmatrix}0&1\\\\0&0\\end{bmatrix}$. \n",
    "\n",
    "Recall that $\\mathbf A$ is the *system dynamics matrix*. It describes a set of linear differential equations. From it we must compute the state transition matrix $\\mathbf F$. $\\mathbf F$ describes a discrete set of linear equations which compute $\\mathbf x$ for a discrete time step $\\Delta t$.\n",
    "\n",
    "A common way to compute $\\mathbf F$ is to use the power series expansion of the matrix exponential:\n",
    "\n",
    "$$\\mathbf F(\\Delta t) = e^{\\mathbf A\\Delta t} = \\mathbf{I} + \\mathbf A\\Delta t  + \\frac{(\\mathbf A\\Delta t)^2}{2!} + \\frac{(\\mathbf A \\Delta t)^3}{3!} + ... $$\n",
    "\n",
    "\n",
    "$\\mathbf A^2 = \\begin{bmatrix}0&0\\\\0&0\\end{bmatrix}$, so all higher powers of $\\mathbf A$ are also $\\mathbf{0}$. Thus the power series expansion is:\n",
    "\n",
    "$$\n",
    "\\begin{aligned}\n",
    "\\mathbf F &=\\mathbf{I} + \\mathbf At + \\mathbf{0} \\\\\n",
    "&= \\begin{bmatrix}1&0\\\\0&1\\end{bmatrix} + \\begin{bmatrix}0&1\\\\0&0\\end{bmatrix}\\Delta t\\\\\n",
    "\\mathbf F &= \\begin{bmatrix}1&\\Delta t\\\\0&1\\end{bmatrix}\n",
    "\\end{aligned}$$\n",
    "\n",
    "This is the same result used by the kinematic equations! This exercise was unnecessary other than to illustrate finding the state transition matrix from linear differential equations. We will conclude the chapter with an example that will require the use of this technique."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Design the Measurement Model\n",
    "\n",
    "The measurement function takes the state estimate of the prior $\\bar{\\mathbf x}$ and turn it into a measurement of the slant range distance. We use the Pythagorean theorem to derive:\n",
    "\n",
    "$$h(\\bar{\\mathbf x}) = \\sqrt{x^2 + y^2}$$\n",
    "\n",
    "The relationship between the slant distance and the position on the ground is nonlinear due to the square root. We linearize it by evaluating its partial derivative at $\\mathbf x_t$:\n",
    "\n",
    "$$\n",
    "\\mathbf H = \\frac{\\partial{h(\\bar{\\mathbf x})}}{\\partial{\\bar{\\mathbf x}}}\\biggr|_{\\bar{\\mathbf x}_t}\n",
    "$$\n",
    "\n",
    "The partial derivative of a matrix is called a Jacobian, and takes the form \n",
    "\n",
    "$$\\frac{\\partial \\mathbf H}{\\partial \\bar{\\mathbf x}} = \n",
    "\\begin{bmatrix}\n",
    "\\frac{\\partial h_1}{\\partial x_1} & \\frac{\\partial h_1}{\\partial x_2} &\\dots \\\\\n",
    "\\frac{\\partial h_2}{\\partial x_1} & \\frac{\\partial h_2}{\\partial x_2} &\\dots \\\\\n",
    "\\vdots & \\vdots\n",
    "\\end{bmatrix}\n",
    "$$\n",
    "\n",
    "In other words, each element in the matrix is the partial derivative of the function $h$ with respect to the $x$ variables. For our problem we have\n",
    "\n",
    "$$\\mathbf H = \\begin{bmatrix}{\\partial h}/{\\partial x} & {\\partial h}/{\\partial \\dot{x}} & {\\partial h}/{\\partial y}\\end{bmatrix}$$\n",
    "\n",
    "Solving each in turn:\n",
    "\n",
    "$$\\begin{aligned}\n",
    "\\frac{\\partial h}{\\partial x} &= \\frac{\\partial}{\\partial x} \\sqrt{x^2 + y^2} \\\\\n",
    "&= \\frac{x}{\\sqrt{x^2 + y^2}}\n",
    "\\end{aligned}$$\n",
    "\n",
    "and\n",
    "\n",
    "$$\\begin{aligned}\n",
    "\\frac{\\partial h}{\\partial \\dot{x}} &=\n",
    "\\frac{\\partial}{\\partial \\dot{x}} \\sqrt{x^2 + y^2} \\\\ \n",
    "&= 0\n",
    "\\end{aligned}$$\n",
    "\n",
    "and\n",
    "\n",
    "$$\\begin{aligned}\n",
    "\\frac{\\partial h}{\\partial y} &= \\frac{\\partial}{\\partial y} \\sqrt{x^2 + y^2} \\\\ \n",
    "&= \\frac{y}{\\sqrt{x^2 + y^2}}\n",
    "\\end{aligned}$$\n",
    "\n",
    "giving us \n",
    "\n",
    "$$\\mathbf H = \n",
    "\\begin{bmatrix}\n",
    "\\frac{x}{\\sqrt{x^2 + y^2}} & \n",
    "0 &\n",
    "&\n",
    "\\frac{y}{\\sqrt{x^2 + y^2}}\n",
    "\\end{bmatrix}$$\n",
    "\n",
    "This may seem daunting, so step back and recognize that all of this math is doing something very simple. We have an equation for the slant range to the airplane which is nonlinear. The Kalman filter only works with linear equations, so we need to find a linear equation that approximates $\\mathbf H$. As we discussed above, finding the slope of a nonlinear equation at a given point is a good approximation. For the Kalman filter, the 'given point' is the state variable $\\mathbf x$ so we need to take the derivative of the slant range with respect to $\\mathbf x$. For the linear Kalman filter $\\mathbf H$ was a constant that we computed prior to running the filter. For the EKF $\\mathbf H$ is updated at each step as the evaluation point $\\bar{\\mathbf x}$ changes at each epoch.\n",
    "\n",
    "To make this more concrete, let's now write a Python function that computes the Jacobian of $h$ for this problem."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from math import sqrt\n",
    "def HJacobian_at(x):\n",
    "    \"\"\" compute Jacobian of H matrix at x \"\"\"\n",
    "\n",
    "    horiz_dist = x[0]\n",
    "    altitude   = x[2]\n",
    "    denom = sqrt(horiz_dist**2 + altitude**2)\n",
    "    return array ([[horiz_dist/denom, 0., altitude/denom]])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, let's provide the code for $h(\\bar{\\mathbf x})$:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def hx(x):\n",
    "    \"\"\" compute measurement for slant range that\n",
    "    would correspond to state x.\n",
    "    \"\"\"\n",
    "    \n",
    "    return (x[0]**2 + x[2]**2) ** 0.5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's write a simulation for our radar."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from numpy.random import randn\n",
    "import math\n",
    "\n",
    "class RadarSim:\n",
    "    \"\"\" Simulates the radar signal returns from an object\n",
    "    flying at a constant altityude and velocity in 1D. \n",
    "    \"\"\"\n",
    "    \n",
    "    def __init__(self, dt, pos, vel, alt):\n",
    "        self.pos = pos\n",
    "        self.vel = vel\n",
    "        self.alt = alt\n",
    "        self.dt = dt\n",
    "        \n",
    "    def get_range(self):\n",
    "        \"\"\" Returns slant range to the object. Call once \n",
    "        for each new measurement at dt time from last call.\n",
    "        \"\"\"\n",
    "        \n",
    "        # add some process noise to the system\n",
    "        self.vel = self.vel  + .1*randn()\n",
    "        self.alt = self.alt + .1*randn()\n",
    "        self.pos = self.pos + self.vel*self.dt\n",
    "    \n",
    "        # add measurement noise\n",
    "        err = self.pos * 0.05*randn()\n",
    "        slant_dist = math.sqrt(self.pos**2 + self.alt**2)\n",
    "        \n",
    "        return slant_dist + err"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Design Process and Measurement Noise\n",
    "\n",
    "The radar measures the range to a target. We will use $\\sigma_{range}= 5$ meters for the noise. This gives us\n",
    "\n",
    "$$\\mathbf R = \\begin{bmatrix}\\sigma_{range}^2\\end{bmatrix} = \\begin{bmatrix}25\\end{bmatrix}$$\n",
    "\n",
    "\n",
    "The design of $\\mathbf Q$ requires some discussion. The state $\\mathbf x= \\begin{bmatrix}x & \\dot x & y\\end{bmatrix}^\\mathtt{T}$. The first two elements are position (down range distance) and velocity, so we can use `Q_discrete_white_noise` noise to compute the values for the upper left hand side of $\\mathbf Q$. The third element of  $\\mathbf x$ is altitude, which we are assuming is independent of the down range distance. That leads us to a block design of $\\mathbf Q$ of:\n",
    "\n",
    "$$\\mathbf Q = \\begin{bmatrix}\\mathbf Q_\\mathtt{x} & 0 \\\\ 0 & \\mathbf Q_\\mathtt{y}\\end{bmatrix}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Implementation\n",
    "\n",
    "`FilterPy` provides the class `ExtendedKalmanFilter`. It works similarly to the `KalmanFilter` class we have been using, except that it allows you to provide a function that computes the Jacobian of $\\mathbf H$ and the function $h(\\mathbf x)$. \n",
    "\n",
    "We start by importing the filter and creating it. The dimension of `x` is 3 and `z` has dimension 1.\n",
    "\n",
    "```python\n",
    "from filterpy.kalman import ExtendedKalmanFilter\n",
    "\n",
    "rk = ExtendedKalmanFilter(dim_x=3, dim_z=1)\n",
    "```\n",
    "We create the radar simulator:\n",
    "```python\n",
    "radar = RadarSim(dt, pos=0., vel=100., alt=1000.)\n",
    "```\n",
    "We will initialize the filter near the airplane's actual position:\n",
    "\n",
    "```python\n",
    "rk.x = array([radar.pos, radar.vel-10, radar.alt+100])\n",
    "```\n",
    "\n",
    "We assign the system matrix using the first term of the Taylor series expansion we computed above:\n",
    "\n",
    "```python\n",
    "dt = 0.05\n",
    "rk.F = eye(3) + array([[0, 1, 0],\n",
    "                       [0, 0, 0],\n",
    "                       [0, 0, 0]])*dt\n",
    "```\n",
    "\n",
    "After assigning reasonable values to $\\mathbf R$, $\\mathbf Q$, and $\\mathbf P$ we can run the filter with a simple loop. We pass the functions for computing the Jacobian of $\\mathbf  H$ and $h(x)$ into the `update` method.\n",
    "\n",
    "```python\n",
    "for i in range(int(20/dt)):\n",
    "    z = radar.get_range()\n",
    "    rk.update(array([z]), HJacobian_at, hx)\n",
    "    rk.predict()\n",
    "```\n",
    "\n",
    "Adding some boilerplate code to save and plot the results we get:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from filterpy.common import Q_discrete_white_noise\n",
    "from filterpy.kalman import ExtendedKalmanFilter\n",
    "from numpy import eye, array, asarray\n",
    "import numpy as np\n",
    "\n",
    "dt = 0.05\n",
    "rk = ExtendedKalmanFilter(dim_x=3, dim_z=1)\n",
    "radar = RadarSim(dt, pos=0., vel=100., alt=1000.)\n",
    "\n",
    "# make an imperfect starting guess\n",
    "rk.x = array([radar.pos-100, radar.vel+100, radar.alt+1000])\n",
    "\n",
    "rk.F = eye(3) + array([[0, 1, 0],\n",
    "                       [0, 0, 0],\n",
    "                       [0, 0, 0]]) * dt\n",
    "\n",
    "range_std = 5. # meters\n",
    "rk.R = np.diag([range_std**2])\n",
    "rk.Q[0:2, 0:2] = Q_discrete_white_noise(2, dt=dt, var=0.1)\n",
    "rk.Q[2,2] = 0.1\n",
    "rk.P *= 50\n",
    "\n",
    "xs, track = [], []\n",
    "for i in range(int(20/dt)):\n",
    "    z = radar.get_range()\n",
    "    track.append((radar.pos, radar.vel, radar.alt))\n",
    "    \n",
    "    rk.update(array([z]), HJacobian_at, hx)\n",
    "    xs.append(rk.x)\n",
    "    rk.predict()\n",
    "\n",
    "xs = asarray(xs)\n",
    "track = asarray(track)\n",
    "time = np.arange(0, len(xs)*dt, dt)\n",
    "ekf_internal.plot_radar(xs, track, time)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using SymPy to compute Jacobians\n",
    "\n",
    "Depending on your experience with derivatives you may have found the computation of the Jacobian difficult. Even if you found it easy, a slightly more difficult problem easily leads to very difficult computations.\n",
    "\n",
    "As explained in Appendix A, we can use the SymPy package to compute the Jacobian for us."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle \\left[\\begin{matrix}x\\\\x_{vel}\\\\y\\end{matrix}\\right]$"
      ],
      "text/plain": [
       "⎡ x  ⎤\n",
       "⎢    ⎥\n",
       "⎢xᵥₑₗ⎥\n",
       "⎢    ⎥\n",
       "⎣ y  ⎦"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/latex": [
       "$\\displaystyle \\left[\\begin{matrix}\\frac{x}{\\sqrt{x^{2} + y^{2}}} & 0 & \\frac{y}{\\sqrt{x^{2} + y^{2}}}\\end{matrix}\\right]$"
      ],
      "text/plain": [
       "⎡     x                y      ⎤\n",
       "⎢────────────  0  ────────────⎥\n",
       "⎢   _________        _________⎥\n",
       "⎢  ╱  2    2        ╱  2    2 ⎥\n",
       "⎣╲╱  x  + y       ╲╱  x  + y  ⎦"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import sympy\n",
    "from IPython.display import display\n",
    "sympy.init_printing(use_latex='mathjax')\n",
    "\n",
    "x, x_vel, y = sympy.symbols('x, x_vel y')\n",
    "\n",
    "H = sympy.Matrix([sympy.sqrt(x**2 + y**2)])\n",
    "\n",
    "state = sympy.Matrix([x, x_vel, y])\n",
    "J = H.jacobian(state)\n",
    "\n",
    "display(state)\n",
    "display(J)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This result is the same as the result we computed above, and with much less effort on our part!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Robot Localization\n",
    "\n",
    "It's time to try a real problem. I warn you that this section is difficult. However, most books choose simple, textbook problems with simple answers, and you are left wondering how to solve a real world problem. \n",
    "\n",
    "We will consider the problem of robot localization. We already implemented this in the **Unscented Kalman Filter** chapter, and I recommend you read it now if you haven't already.  In this scenario we have a robot that is moving through a landscape using a sensor to detect landmarks. This could be a self driving car using computer vision to identify trees, buildings, and other landmarks. It might be one of those small robots that vacuum your house, or a robot in a warehouse.\n",
    "\n",
    "The robot has 4 wheels in the same configuration used by automobiles. It maneuvers by pivoting the front wheels. This causes the robot to pivot around the rear axle while moving forward. This is nonlinear behavior which we will have to model. \n",
    "\n",
    "The robot has a sensor that measures the range and bearing to known targets in the landscape. This is nonlinear because computing a position from a range and bearing requires square roots and trigonometry. \n",
    "\n",
    "Both the process model and measurement models are nonlinear. The EKF accommodates both, so we provisionally conclude that the EKF is a viable choice for this problem."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Robot Motion Model\n",
    "\n",
    "At a first approximation an automobile steers by pivoting the front tires while moving forward. The front of the car moves in the direction that the wheels are pointing while pivoting around the rear tires. This simple description is complicated by issues such as slippage due to friction, the differing behavior of the rubber tires at different speeds, and the need for the outside tire to travel a different radius than the inner tire. Accurately modeling steering requires a complicated set of differential equations. \n",
    "\n",
    "For lower speed robotic applications a simpler *bicycle model* has been found to perform well. This is a depiction of the model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ekf_internal.plot_bicycle()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the **Unscented Kalman Filter** chapter we derived these equations:\n",
    "\n",
    "$$\\begin{aligned} \n",
    "\\beta &= \\frac d w \\tan(\\alpha) \\\\\n",
    "x &= x - R\\sin(\\theta) + R\\sin(\\theta + \\beta) \\\\\n",
    "y &= y + R\\cos(\\theta) - R\\cos(\\theta + \\beta) \\\\\n",
    "\\theta &= \\theta + \\beta\n",
    "\\end{aligned}\n",
    "$$\n",
    "\n",
    "where $\\theta$ is the robot's heading.\n",
    "\n",
    "You do not need to understand this model in detail if you are not interested in steering models. The important thing to recognize is that our motion model is nonlinear, and we will need to deal with that with our Kalman filter."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Design the State Variables\n",
    "\n",
    "For our filter we will maintain the position $x,y$ and orientation $\\theta$ of the robot:\n",
    "\n",
    "$$\\mathbf x = \\begin{bmatrix}x \\\\ y \\\\ \\theta\\end{bmatrix}$$\n",
    "\n",
    "Our control input $\\mathbf u$ is the velocity $v$ and steering angle $\\alpha$:\n",
    "\n",
    "$$\\mathbf u = \\begin{bmatrix}v \\\\ \\alpha\\end{bmatrix}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Design the System Model\n",
    "\n",
    "We model our system as a nonlinear motion model plus noise.\n",
    "\n",
    "$$\\bar x = f(x, u) + \\mathcal{N}(0, Q)$$\n",
    "\n",
    "\n",
    "\n",
    "Using the motion model for a robot that we created above, we can expand this to\n",
    "\n",
    "$$\\bar{\\begin{bmatrix}x\\\\y\\\\\\theta\\end{bmatrix}} = \\begin{bmatrix}x\\\\y\\\\\\theta\\end{bmatrix} + \n",
    "\\begin{bmatrix}- R\\sin(\\theta) + R\\sin(\\theta + \\beta) \\\\\n",
    "R\\cos(\\theta) - R\\cos(\\theta + \\beta) \\\\\n",
    "\\beta\\end{bmatrix}$$\n",
    "\n",
    "We find The $\\mathbf F$ by taking the Jacobian of $f(x,u)$.\n",
    "\n",
    "$$\\mathbf F = \\frac{\\partial f(x, u)}{\\partial x} =\\begin{bmatrix}\n",
    "\\frac{\\partial f_1}{\\partial x} & \n",
    "\\frac{\\partial f_1}{\\partial y} &\n",
    "\\frac{\\partial f_1}{\\partial \\theta}\\\\\n",
    "\\frac{\\partial f_2}{\\partial x} & \n",
    "\\frac{\\partial f_2}{\\partial y} &\n",
    "\\frac{\\partial f_2}{\\partial \\theta} \\\\\n",
    "\\frac{\\partial f_3}{\\partial x} & \n",
    "\\frac{\\partial f_3}{\\partial y} &\n",
    "\\frac{\\partial f_3}{\\partial \\theta}\n",
    "\\end{bmatrix}\n",
    "$$\n",
    "\n",
    "When we calculate these we get\n",
    "\n",
    "$$\\mathbf F = \\begin{bmatrix}\n",
    "1 & 0 & -R\\cos(\\theta) + R\\cos(\\theta+\\beta) \\\\\n",
    "0 & 1 & -R\\sin(\\theta) + R\\sin(\\theta+\\beta) \\\\\n",
    "0 & 0 & 1\n",
    "\\end{bmatrix}$$\n",
    "\n",
    "We can double check our work with SymPy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle \\left[\\begin{matrix}1 & 0 & - \\frac{w \\cos{\\left(\\theta \\right)}}{\\tan{\\left(\\alpha \\right)}} + \\frac{w \\cos{\\left(\\frac{t v \\tan{\\left(\\alpha \\right)}}{w} + \\theta \\right)}}{\\tan{\\left(\\alpha \\right)}}\\\\0 & 1 & - \\frac{w \\sin{\\left(\\theta \\right)}}{\\tan{\\left(\\alpha \\right)}} + \\frac{w \\sin{\\left(\\frac{t v \\tan{\\left(\\alpha \\right)}}{w} + \\theta \\right)}}{\\tan{\\left(\\alpha \\right)}}\\\\0 & 0 & 1\\end{matrix}\\right]$"
      ],
      "text/plain": [
       "⎡                        ⎛t⋅v⋅tan(α)    ⎞⎤\n",
       "⎢                   w⋅cos⎜────────── + θ⎟⎥\n",
       "⎢        w⋅cos(θ)        ⎝    w         ⎠⎥\n",
       "⎢1  0  - ──────── + ─────────────────────⎥\n",
       "⎢         tan(α)            tan(α)       ⎥\n",
       "⎢                                        ⎥\n",
       "⎢                        ⎛t⋅v⋅tan(α)    ⎞⎥\n",
       "⎢                   w⋅sin⎜────────── + θ⎟⎥\n",
       "⎢        w⋅sin(θ)        ⎝    w         ⎠⎥\n",
       "⎢0  1  - ──────── + ─────────────────────⎥\n",
       "⎢         tan(α)            tan(α)       ⎥\n",
       "⎢                                        ⎥\n",
       "⎣0  0                  1                 ⎦"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import sympy\n",
    "from sympy.abc import alpha, x, y, v, w, R, theta\n",
    "from sympy import symbols, Matrix\n",
    "sympy.init_printing(use_latex=\"mathjax\", fontsize='16pt')\n",
    "time = symbols('t')\n",
    "d = v*time\n",
    "beta = (d/w)*sympy.tan(alpha)\n",
    "r = w/sympy.tan(alpha)\n",
    "\n",
    "fxu = Matrix([[x-r*sympy.sin(theta) + r*sympy.sin(theta+beta)],\n",
    "              [y+r*sympy.cos(theta)- r*sympy.cos(theta+beta)],\n",
    "              [theta+beta]])\n",
    "F = fxu.jacobian(Matrix([x, y, theta]))\n",
    "F"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That looks a bit complicated. We can use SymPy to substitute terms:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle \\left[\\begin{matrix}1 & 0 & - R \\cos{\\left(\\theta \\right)} + R \\cos{\\left(\\beta + \\theta \\right)}\\\\0 & 1 & - R \\sin{\\left(\\theta \\right)} + R \\sin{\\left(\\beta + \\theta \\right)}\\\\0 & 0 & 1\\end{matrix}\\right]$"
      ],
      "text/plain": [
       "⎡1  0  -R⋅cos(θ) + R⋅cos(β + θ)⎤\n",
       "⎢                              ⎥\n",
       "⎢0  1  -R⋅sin(θ) + R⋅sin(β + θ)⎥\n",
       "⎢                              ⎥\n",
       "⎣0  0             1            ⎦"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# reduce common expressions\n",
    "B, R = symbols('beta, R')\n",
    "F = F.subs((d/w)*sympy.tan(alpha), B)\n",
    "F.subs(w/sympy.tan(alpha), R)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This form  verifies that the computation of the Jacobian is correct.\n",
    "\n",
    "Now we can turn our attention to the noise. Here, the noise is in our control input, so it is in *control space*. In other words, we command a specific velocity and steering angle, but we need to convert that into errors in $x, y, \\theta$. In a real system this might vary depending on velocity, so it will need to be recomputed for every prediction. I will choose this as the noise model; for a real robot you will need to choose a model that accurately depicts the error in your system. \n",
    "\n",
    "$$\\mathbf{M} = \\begin{bmatrix}\\sigma_{vel}^2 & 0 \\\\ 0 & \\sigma_\\alpha^2\\end{bmatrix}$$\n",
    "\n",
    "If this was a linear problem we would convert from control space to state space using the by now familiar $\\mathbf{FMF}^\\mathsf T$ form. Since our motion model is nonlinear we do not try to find a closed form solution to this, but instead linearize it with a Jacobian which we will name $\\mathbf{V}$. \n",
    "\n",
    "$$\\mathbf{V} = \\frac{\\partial f(x, u)}{\\partial u} \\begin{bmatrix}\n",
    "\\frac{\\partial f_1}{\\partial v} & \\frac{\\partial f_1}{\\partial \\alpha} \\\\\n",
    "\\frac{\\partial f_2}{\\partial v} & \\frac{\\partial f_2}{\\partial \\alpha} \\\\\n",
    "\\frac{\\partial f_3}{\\partial v} & \\frac{\\partial f_3}{\\partial \\alpha}\n",
    "\\end{bmatrix}$$\n",
    "\n",
    "These partial derivatives become very difficult to work with. Let's compute them with SymPy. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle \\left[\\begin{matrix}t \\cos{\\left(\\beta + \\theta \\right)} & \\frac{d \\left(\\tan^{2}{\\left(\\alpha \\right)} + 1\\right) \\cos{\\left(\\beta + \\theta \\right)}}{\\tan{\\left(\\alpha \\right)}} - \\frac{w \\left(- \\tan^{2}{\\left(\\alpha \\right)} - 1\\right) \\sin{\\left(\\theta \\right)}}{\\tan^{2}{\\left(\\alpha \\right)}} + \\frac{w \\left(- \\tan^{2}{\\left(\\alpha \\right)} - 1\\right) \\sin{\\left(\\beta + \\theta \\right)}}{\\tan^{2}{\\left(\\alpha \\right)}}\\\\t \\sin{\\left(\\beta + \\theta \\right)} & \\frac{d \\left(\\tan^{2}{\\left(\\alpha \\right)} + 1\\right) \\sin{\\left(\\beta + \\theta \\right)}}{\\tan{\\left(\\alpha \\right)}} + \\frac{w \\left(- \\tan^{2}{\\left(\\alpha \\right)} - 1\\right) \\cos{\\left(\\theta \\right)}}{\\tan^{2}{\\left(\\alpha \\right)}} - \\frac{w \\left(- \\tan^{2}{\\left(\\alpha \\right)} - 1\\right) \\cos{\\left(\\beta + \\theta \\right)}}{\\tan^{2}{\\left(\\alpha \\right)}}\\\\\\frac{t}{R} & \\frac{d \\left(\\tan^{2}{\\left(\\alpha \\right)} + 1\\right)}{w}\\end{matrix}\\right]$"
      ],
      "text/plain": [
       "⎡                ⎛   2       ⎞                ⎛     2       ⎞            ⎛    \n",
       "⎢              d⋅⎝tan (α) + 1⎠⋅cos(β + θ)   w⋅⎝- tan (α) - 1⎠⋅sin(θ)   w⋅⎝- ta\n",
       "⎢t⋅cos(β + θ)  ────────────────────────── - ──────────────────────── + ───────\n",
       "⎢                        tan(α)                        2                      \n",
       "⎢                                                   tan (α)                   \n",
       "⎢                                                                             \n",
       "⎢                ⎛   2       ⎞                ⎛     2       ⎞            ⎛    \n",
       "⎢              d⋅⎝tan (α) + 1⎠⋅sin(β + θ)   w⋅⎝- tan (α) - 1⎠⋅cos(θ)   w⋅⎝- ta\n",
       "⎢t⋅sin(β + θ)  ────────────────────────── + ──────────────────────── - ───────\n",
       "⎢                        tan(α)                        2                      \n",
       "⎢                                                   tan (α)                   \n",
       "⎢                                                                             \n",
       "⎢                                                  ⎛   2       ⎞              \n",
       "⎢     t                                          d⋅⎝tan (α) + 1⎠              \n",
       "⎢     ─                                          ───────────────              \n",
       "⎣     R                                                 w                     \n",
       "\n",
       " 2       ⎞           ⎤\n",
       "n (α) - 1⎠⋅sin(β + θ)⎥\n",
       "─────────────────────⎥\n",
       "      2              ⎥\n",
       "   tan (α)           ⎥\n",
       "                     ⎥\n",
       " 2       ⎞           ⎥\n",
       "n (α) - 1⎠⋅cos(β + θ)⎥\n",
       "─────────────────────⎥\n",
       "      2              ⎥\n",
       "   tan (α)           ⎥\n",
       "                     ⎥\n",
       "                     ⎥\n",
       "                     ⎥\n",
       "                     ⎥\n",
       "                     ⎦"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "V = fxu.jacobian(Matrix([v, alpha]))\n",
    "V = V.subs(sympy.tan(alpha)/w, 1/R) \n",
    "V = V.subs(time*v/R, B)\n",
    "V = V.subs(time*v, 'd')\n",
    "V"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This should give you an appreciation of how quickly the EKF become mathematically intractable. \n",
    "\n",
    "This gives us the final form of our prediction equations:\n",
    "\n",
    "$$\\begin{aligned}\n",
    "\\mathbf{\\bar x} &= \\mathbf x + \n",
    "\\begin{bmatrix}- R\\sin(\\theta) + R\\sin(\\theta + \\beta) \\\\\n",
    "R\\cos(\\theta) - R\\cos(\\theta + \\beta) \\\\\n",
    "\\beta\\end{bmatrix}\\\\\n",
    "\\mathbf{\\bar P} &=\\mathbf{FPF}^{\\mathsf T} + \\mathbf{VMV}^{\\mathsf T}\n",
    "\\end{aligned}$$\n",
    "\n",
    "This form of linearization is not the only way to predict $\\mathbf x$. For example, we could use a numerical integration technique such as *Runge Kutta* to compute the movement\n",
    "of the robot. This will be required if the time step is relatively large. Things are not as cut and dried with the EKF as for the Kalman filter. For a real problem you have to carefully model your system with differential equations and then determine the most appropriate way to solve that system. The correct approach depends on the accuracy you require, how nonlinear the equations are, your processor budget, and numerical stability concerns."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Design the Measurement Model\n",
    "\n",
    "The robot's sensor provides a noisy bearing and range measurement to multiple known locations in the landscape. The measurement model must convert the state $\\begin{bmatrix}x & y&\\theta\\end{bmatrix}^\\mathsf T$ into a range and bearing to the landmark. If $\\mathbf p$ \n",
    "is the position of a landmark, the range $r$ is\n",
    "\n",
    "$$r = \\sqrt{(p_x - x)^2 + (p_y - y)^2}$$\n",
    "\n",
    "The sensor provides bearing relative to the orientation of the robot, so we must subtract the robot's orientation from the bearing to get the sensor reading, like so:\n",
    "\n",
    "$$\\phi = \\arctan(\\frac{p_y - y}{p_x - x}) - \\theta$$\n",
    "\n",
    "\n",
    "Thus our measurement model $h$ is\n",
    "\n",
    "\n",
    "$$\\begin{aligned}\n",
    "\\mathbf z& = h(\\bar{\\mathbf x}, \\mathbf p) &+ \\mathcal{N}(0, R)\\\\\n",
    "&= \\begin{bmatrix}\n",
    "\\sqrt{(p_x - x)^2 + (p_y - y)^2} \\\\\n",
    "\\arctan(\\frac{p_y - y}{p_x - x}) - \\theta \n",
    "\\end{bmatrix} &+ \\mathcal{N}(0, R)\n",
    "\\end{aligned}$$\n",
    "\n",
    "This is clearly nonlinear, so we need linearize $h$  at $\\mathbf x$ by taking its Jacobian. We compute that with SymPy below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle \\left[\\begin{matrix}\\frac{- p_{x} + x}{\\sqrt{\\left(p_{x} - x\\right)^{2} + \\left(p_{y} - y\\right)^{2}}} & \\frac{- p_{y} + y}{\\sqrt{\\left(p_{x} - x\\right)^{2} + \\left(p_{y} - y\\right)^{2}}} & 0\\\\- \\frac{- p_{y} + y}{\\left(p_{x} - x\\right)^{2} + \\left(p_{y} - y\\right)^{2}} & - \\frac{p_{x} - x}{\\left(p_{x} - x\\right)^{2} + \\left(p_{y} - y\\right)^{2}} & -1\\end{matrix}\\right]$"
      ],
      "text/plain": [
       "⎡          -pₓ + x                      -p_y + y             ⎤\n",
       "⎢───────────────────────────  ───────────────────────────  0 ⎥\n",
       "⎢   ________________________     ________________________    ⎥\n",
       "⎢  ╱         2            2     ╱         2            2     ⎥\n",
       "⎢╲╱  (pₓ - x)  + (p_y - y)    ╲╱  (pₓ - x)  + (p_y - y)      ⎥\n",
       "⎢                                                            ⎥\n",
       "⎢       -(-p_y + y)                   -(pₓ - x)              ⎥\n",
       "⎢  ──────────────────────       ──────────────────────     -1⎥\n",
       "⎢          2            2               2            2       ⎥\n",
       "⎣  (pₓ - x)  + (p_y - y)        (pₓ - x)  + (p_y - y)        ⎦"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "px, py = symbols('p_x, p_y')\n",
    "z = Matrix([[sympy.sqrt((px-x)**2 + (py-y)**2)],\n",
    "            [sympy.atan2(py-y, px-x) - theta]])\n",
    "z.jacobian(Matrix([x, y, theta]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we need to write that as a Python function. For example we might write:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "from math import sqrt\n",
    "\n",
    "def H_of(x, landmark_pos):\n",
    "    \"\"\" compute Jacobian of H matrix where h(x) computes \n",
    "    the range and bearing to a landmark for state x \"\"\"\n",
    "\n",
    "    px = landmark_pos[0]\n",
    "    py = landmark_pos[1]\n",
    "    hyp = (px - x[0, 0])**2 + (py - x[1, 0])**2\n",
    "    dist = sqrt(hyp)\n",
    "\n",
    "    H = array(\n",
    "        [[-(px - x[0, 0]) / dist, -(py - x[1, 0]) / dist, 0],\n",
    "         [ (py - x[1, 0]) / hyp,  -(px - x[0, 0]) / hyp, -1]])\n",
    "    return H"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We also need to define a function that converts the system state into a measurement."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "from math import atan2\n",
    "\n",
    "def Hx(x, landmark_pos):\n",
    "    \"\"\" takes a state variable and returns the measurement\n",
    "    that would correspond to that state.\n",
    "    \"\"\"\n",
    "    px = landmark_pos[0]\n",
    "    py = landmark_pos[1]\n",
    "    dist = sqrt((px - x[0, 0])**2 + (py - x[1, 0])**2)\n",
    "\n",
    "    Hx = array([[dist],\n",
    "                [atan2(py - x[1, 0], px - x[0, 0]) - x[2, 0]]])\n",
    "    return Hx"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Design Measurement Noise\n",
    "\n",
    "It is reasonable to assume that the noise of the range and bearing measurements are independent, hence\n",
    "\n",
    "$$\\mathbf R=\\begin{bmatrix}\\sigma_{range}^2 & 0 \\\\ 0 & \\sigma_{bearing}^2\\end{bmatrix}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Implementation\n",
    "\n",
    "We will use `FilterPy`'s `ExtendedKalmanFilter` class to implement the filter. Its `predict()` method uses the standard linear equations for the process model. Ours is nonlinear, so we will have to override `predict()` with our own implementation.  I'll want to also use this class to simulate the robot, so I'll add a method `move()` that computes the position of the robot which both `predict()` and my simulation can call.\n",
    "\n",
    "The matrices for the prediction step are quite large. While writing this code I made several errors before I finally got it working. I only found my errors by using SymPy's `evalf` function. `evalf` evaluates a SymPy `Matrix` with specific values for the variables. I decided to demonstrate this technique to you, and used `evalf` in the Kalman filter code. You'll need to understand a couple of points.\n",
    "\n",
    "First, `evalf` uses a dictionary to specify the values. For example, if your matrix contains an `x` and `y`, you can write\n",
    "\n",
    "```python\n",
    "    M.evalf(subs={x:3, y:17})\n",
    "```\n",
    "    \n",
    "to evaluate the matrix for `x=3` and `y=17`. \n",
    "\n",
    "Second, `evalf` returns a `sympy.Matrix` object. Use `numpy.array(M).astype(float)` to convert it to a NumPy array. `numpy.array(M)` creates an array of  type `object`, which is not what you want.\n",
    "\n",
    "Here is the code for the EKF:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "from filterpy.kalman import ExtendedKalmanFilter as EKF\n",
    "from numpy import array, sqrt\n",
    "class RobotEKF(EKF):\n",
    "    def __init__(self, dt, wheelbase, std_vel, std_steer):\n",
    "        EKF.__init__(self, 3, 2, 2)\n",
    "        self.dt = dt\n",
    "        self.wheelbase = wheelbase\n",
    "        self.std_vel = std_vel\n",
    "        self.std_steer = std_steer\n",
    "\n",
    "        a, x, y, v, w, theta, time = symbols(\n",
    "            'a, x, y, v, w, theta, t')\n",
    "        d = v*time\n",
    "        beta = (d/w)*sympy.tan(a)\n",
    "        r = w/sympy.tan(a)\n",
    "    \n",
    "        self.fxu = Matrix(\n",
    "            [[x-r*sympy.sin(theta)+r*sympy.sin(theta+beta)],\n",
    "             [y+r*sympy.cos(theta)-r*sympy.cos(theta+beta)],\n",
    "             [theta+beta]])\n",
    "\n",
    "        self.F_j = self.fxu.jacobian(Matrix([x, y, theta]))\n",
    "        self.V_j = self.fxu.jacobian(Matrix([v, a]))\n",
    "\n",
    "        # save dictionary and it's variables for later use\n",
    "        self.subs = {x: 0, y: 0, v:0, a:0, \n",
    "                     time:dt, w:wheelbase, theta:0}\n",
    "        self.x_x, self.x_y, = x, y \n",
    "        self.v, self.a, self.theta = v, a, theta\n",
    "\n",
    "    def predict(self, u):\n",
    "        self.x = self.move(self.x, u, self.dt)\n",
    "\n",
    "        self.subs[self.theta] = self.x[2, 0]\n",
    "        self.subs[self.v] = u[0]\n",
    "        self.subs[self.a] = u[1]\n",
    "\n",
    "        F = array(self.F_j.evalf(subs=self.subs)).astype(float)\n",
    "        V = array(self.V_j.evalf(subs=self.subs)).astype(float)\n",
    "\n",
    "        # covariance of motion noise in control space\n",
    "        M = array([[self.std_vel*u[0]**2, 0], \n",
    "                   [0, self.std_steer**2]])\n",
    "\n",
    "        self.P = np.dot(F, self.P).dot(F.T) + np.dot(V, M).dot(V.T)\n",
    "\n",
    "    def move(self, x, u, dt):\n",
    "        hdg = x[2, 0]\n",
    "        vel = u[0]\n",
    "        steering_angle = u[1]\n",
    "        dist = vel * dt\n",
    "\n",
    "        if abs(steering_angle) > 0.001: # is robot turning?\n",
    "            beta = (dist / self.wheelbase) * tan(steering_angle)\n",
    "            r = self.wheelbase / tan(steering_angle) # radius\n",
    "\n",
    "            dx = np.array([[-r*sin(hdg) + r*sin(hdg + beta)], \n",
    "                           [r*cos(hdg) - r*cos(hdg + beta)], \n",
    "                           [beta]])\n",
    "        else: # moving in straight line\n",
    "            dx = np.array([[dist*cos(hdg)], \n",
    "                           [dist*sin(hdg)], \n",
    "                           [0]])\n",
    "        return x + dx"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we have another issue to handle. The residual is notionally computed as $y = z - h(x)$ but this will not work because our measurement contains an angle in it. Suppose z has a bearing of $1^\\circ$ and $h(x)$ has a bearing of $359^\\circ$. Naively subtracting them would yield a angular difference of $-358^\\circ$, whereas the correct value is $2^\\circ$. We have to write code to correctly compute the bearing residual."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "def residual(a, b):\n",
    "    \"\"\" compute residual (a-b) between measurements containing \n",
    "    [range, bearing]. Bearing is normalized to [-pi, pi)\"\"\"\n",
    "    y = a - b\n",
    "    y[1] = y[1] % (2 * np.pi)    # force in range [0, 2 pi)\n",
    "    if y[1] > np.pi:             # move to [-pi, pi)\n",
    "        y[1] -= 2 * np.pi\n",
    "    return y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The rest of the code runs the simulation and plots the results, and shouldn't need too much comment by now. I create a variable `landmarks` that contains the landmark coordinates. I update the simulated robot position 10 times a second, but run the EKF only once per second. This is for two reasons. First, we are not using Runge Kutta to integrate the differental equations of motion, so a narrow time step allows our simulation to be more accurate. Second, it is fairly normal in embedded systems to have limited processing speed. This forces you to run your Kalman filter only as frequently as absolutely needed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "from filterpy.stats import plot_covariance_ellipse\n",
    "from math import sqrt, tan, cos, sin, atan2\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "dt = 1.0\n",
    "\n",
    "def z_landmark(lmark, sim_pos, std_rng, std_brg):\n",
    "    x, y = sim_pos[0, 0], sim_pos[1, 0]\n",
    "    d = np.sqrt((lmark[0] - x)**2 + (lmark[1] - y)**2)  \n",
    "    a = atan2(lmark[1] - y, lmark[0] - x) - sim_pos[2, 0]\n",
    "    z = np.array([[d + randn()*std_rng],\n",
    "                  [a + randn()*std_brg]])\n",
    "    return z\n",
    "\n",
    "def ekf_update(ekf, z, landmark):\n",
    "    ekf.update(z, HJacobian=H_of, Hx=Hx, \n",
    "               residual=residual,\n",
    "               args=(landmark), hx_args=(landmark))\n",
    "    \n",
    "                \n",
    "def run_localization(landmarks, std_vel, std_steer, \n",
    "                     std_range, std_bearing,\n",
    "                     step=10, ellipse_step=20, ylim=None):\n",
    "    ekf = RobotEKF(dt, wheelbase=0.5, std_vel=std_vel, \n",
    "                   std_steer=std_steer)\n",
    "    ekf.x = array([[2, 6, .3]]).T # x, y, steer angle\n",
    "    ekf.P = np.diag([.1, .1, .1])\n",
    "    ekf.R = np.diag([std_range**2, std_bearing**2])\n",
    "\n",
    "    sim_pos = ekf.x.copy() # simulated position\n",
    "    # steering command (vel, steering angle radians)\n",
    "    u = array([1.1, .01]) \n",
    "\n",
    "    plt.figure()\n",
    "    plt.scatter(landmarks[:, 0], landmarks[:, 1],\n",
    "                marker='s', s=60)\n",
    "    \n",
    "    track = []\n",
    "    for i in range(200):\n",
    "        sim_pos = ekf.move(sim_pos, u, dt/10.) # simulate robot\n",
    "        track.append(sim_pos)\n",
    "\n",
    "        if i % step == 0:\n",
    "            ekf.predict(u=u)\n",
    "\n",
    "            if i % ellipse_step == 0:\n",
    "                plot_covariance_ellipse(\n",
    "                    (ekf.x[0,0], ekf.x[1,0]), ekf.P[0:2, 0:2], \n",
    "                     std=6, facecolor='k', alpha=0.3)\n",
    "\n",
    "            x, y = sim_pos[0, 0], sim_pos[1, 0]\n",
    "            for lmark in landmarks:\n",
    "                z = z_landmark(lmark, sim_pos,\n",
    "                               std_range, std_bearing)\n",
    "                ekf_update(ekf, z, lmark)\n",
    "\n",
    "            if i % ellipse_step == 0:\n",
    "                plot_covariance_ellipse(\n",
    "                    (ekf.x[0,0], ekf.x[1,0]), ekf.P[0:2, 0:2],\n",
    "                    std=6, facecolor='g', alpha=0.8)\n",
    "    track = np.array(track)\n",
    "    plt.plot(track[:, 0], track[:,1], color='k', lw=2)\n",
    "    plt.axis('equal')\n",
    "    plt.title(\"EKF Robot localization\")\n",
    "    if ylim is not None: plt.ylim(*ylim)\n",
    "    plt.show()\n",
    "    return ekf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Final P: [0.026 0.041 0.002]\n"
     ]
    }
   ],
   "source": [
    "landmarks = array([[5, 10], [10, 5], [15, 15]])\n",
    "\n",
    "ekf = run_localization(\n",
    "    landmarks, std_vel=0.1, std_steer=np.radians(1),\n",
    "    std_range=0.3, std_bearing=0.1)\n",
    "print('Final P:', ekf.P.diagonal())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I have plotted the landmarks as solid squares. The path of the robot is drawn with a black line. The covariance ellipses for the predict step are light gray, and the covariances of the update are shown in green. To make them visible at this scale I have set the ellipse boundary at 6$\\sigma$.\n",
    "\n",
    "We can see that there is a lot of uncertainty added by our motion model, and that most of the error in in the direction of motion. We determine that from the shape of the blue ellipses. After a few steps we can see that the filter incorporates the landmark measurements and the errors improve.\n",
    "\n",
    "I used the same initial conditions and landmark locations in the UKF chapter. The UKF achieves much better accuracy in terms of the error ellipse. Both perform roughly as well as far as their estimate for $\\mathbf x$ is concerned. \n",
    "\n",
    "Now let's add another landmark."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Final P: [0.021 0.02  0.002]\n"
     ]
    }
   ],
   "source": [
    "landmarks = array([[5, 10], [10, 5], [15, 15], [20, 5]])\n",
    "\n",
    "ekf = run_localization(\n",
    "    landmarks, std_vel=0.1, std_steer=np.radians(1),\n",
    "    std_range=0.3, std_bearing=0.1)\n",
    "plt.show()\n",
    "print('Final P:', ekf.P.diagonal())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The uncertainly in the estimates near the end of the track are smaller.  We can see the effect that multiple landmarks have on our uncertainty by only using the first two landmarks."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Final P: [0.021 0.045 0.   ]\n"
     ]
    }
   ],
   "source": [
    "ekf = run_localization(\n",
    "    landmarks[0:2], std_vel=1.e-10, std_steer=1.e-10,\n",
    "    std_range=1.4, std_bearing=.05)\n",
    "print('Final P:', ekf.P.diagonal())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The estimate quickly diverges from the robot's path after passing the landmarks. The covariance also grows quickly. Let's see what happens with only one landmark:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Final P: [0.285 0.778 0.004]\n"
     ]
    }
   ],
   "source": [
    "ekf = run_localization(\n",
    "    landmarks[0:1], std_vel=1.e-10, std_steer=1.e-10,\n",
    "    std_range=1.4, std_bearing=.05)\n",
    "print('Final P:', ekf.P.diagonal())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you probably suspected, one landmark produces a very bad result. Conversely, a large number of landmarks allows us to make very accurate estimates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Final P: [0.009 0.008 0.001]\n"
     ]
    }
   ],
   "source": [
    "landmarks = array([[5, 10], [10,  5], [15, 15], [20,  5], [15, 10], \n",
    "                   [10,14], [23, 14], [25, 20], [10, 20]])\n",
    "\n",
    "ekf = run_localization(\n",
    "    landmarks, std_vel=0.1, std_steer=np.radians(1),\n",
    "    std_range=0.3, std_bearing=0.1, ylim=(0, 21))\n",
    "print('Final P:', ekf.P.diagonal())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Discussion\n",
    "\n",
    "I said that this was a real problem, and in some ways it is. I've seen alternative presentations that used robot motion models that led to simpler Jacobians. On the other hand, my model of the movement is also simplistic in several ways. First, it uses a bicycle model. A real car has two sets of tires, and each travels on a different radius. The wheels do not grip the surface perfectly. I also assumed that the robot responds instantaneously to the control input. Sebastian Thrun writes in *Probabilistic Robots* that this simplified model is justified because the filters perform well when used to track real vehicles. The lesson here is that while you have to have a reasonably accurate nonlinear model, it does not need to be perfect to operate well. As a designer you will need to balance the fidelity of your model with the difficulty of the math and the CPU time required to perform the linear algebra. \n",
    "\n",
    "Another way in which this problem was simplistic is that we assumed that we knew the correspondance between the landmarks and measurements. But suppose we are using radar - how would we know that a specific signal return corresponded to a specific building in the local scene? This question hints at SLAM algorithms - simultaneous localization and mapping. SLAM is not the point of this book, so I will not elaborate on this topic. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## UKF vs EKF\n",
    "\n",
    "\n",
    "In the last chapter I used the UKF to solve this problem. The difference in implementation should be very clear. Computing the Jacobians for the state and measurement models was not trivial despite a rudimentary motion model. A different problem could result in a Jacobian which is difficult or impossible to derive analytically. In contrast, the UKF only requires you to provide a function that computes the system motion model and another for the measurement model. \n",
    "\n",
    "There are many cases where the Jacobian cannot be found analytically. The details are beyond the scope of this book, but you will have to use numerical methods to compute the Jacobian. That undertaking is not trivial, and you will spend a significant portion of a master's degree at a STEM school learning techniques to handle such situations. Even then you'll likely only be able to solve problems related to your field - an aeronautical engineer learns a lot about Navier Stokes equations, but not much about modelling chemical reaction rates. \n",
    "\n",
    "So, UKFs are easy. Are they accurate? In practice they often perform better than the EKF. You can find plenty of research papers that prove that the UKF outperforms the EKF in various problem domains. It's not hard to understand why this would be true. The EKF works by linearizing the system model and measurement model at a single point, and the UKF uses $2n+1$ points.\n",
    "\n",
    "Let's look at a specific example. Take $f(x) = x^3$ and pass a Gaussian distribution through it. I will compute an accurate answer using a monte carlo simulation. I generate 50,000 points randomly distributed according to the Gaussian, pass each through $f(x)$, then compute the mean and variance of the result. \n",
    "\n",
    "The EKF linearizes the function by taking the derivative to find the slope at the evaluation point $x$. This slope becomes the linear function that we use to transform the Gaussian. Here is a plot of that."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "actual mean=1.30, std=1.14\n",
      "EKF    mean=1.00, std=0.95\n"
     ]
    }
   ],
   "source": [
    "import kf_book.nonlinear_plots as nonlinear_plots\n",
    "nonlinear_plots.plot_ekf_vs_mc()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The EKF computation is rather inaccurate. In contrast, here is the performance of the UKF:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "actual mean=1.30, std=1.13\n",
      "UKF    mean=1.30, std=1.08\n"
     ]
    }
   ],
   "source": [
    "nonlinear_plots.plot_ukf_vs_mc(alpha=0.001, beta=3., kappa=1.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we can see that the computation of the UKF's mean is accurate to 2 decimal places. The standard deviation is slightly off, but you can also fine tune how the UKF computes the distribution by using the $\\alpha$, $\\beta$, and $\\gamma$ parameters for generating the sigma points. Here I used $\\alpha=0.001$, $\\beta=3$, and $\\gamma=1$. Feel free to modify them to see the result. You should be able to get better results than I did. However, avoid over-tuning the UKF for a specific test. It may perform better for your test case, but worse in general."
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
